Paper
11 September 2024 Electro acupuncture regulate heart function and depression state in rats with dual heart disease
Yuan Ma, Lu Ren, Kexin Zhang
Author Affiliations +
Proceedings Volume 13270, International Conference on Future of Medicine and Biological Information Engineering (MBIE 2024); 1327016 (2024) https://doi.org/10.1117/12.3048284
Event: 2024 International Conference on Future of Medicine and Biological Information Engineering (MBIE 2024), 2024, Shenyang, China
Abstract
Objective: Dual Heart Disease in Traditional Chinese Medicine (DHDTCM) is characterized by suboptimal heart function and depressive-like behaviors. Our hypothesis was that electro-acupuncture (EA) could enhance heart function and alleviate depression in this setting. Methods: Sixty SD rats were randomly divided into five groups: blank, model, EA, traditional Chinese medicine(TCM), and Western medicine(WM). The DHDTCM model was created via Chronic Unpredictable Mild Stress (CUMS) and isoproterenol injection. In the EA group, five points were alternately stimulated by EA. Different treatments were given for 21 days: sertraline in the WM group, an herbal formula in the CM group, and normal saline in the model group. Results: The model was successfully established. EA improved depressive-like behaviors in dual heart disease, as shown in tests. In the OFT, relevant indicators increased in the EA group. EA enhanced cardiac function, as indicated by changes in CD31 and the ECG ST segment. Levels of BDNF and NGF rose. EA regulated HIF-1α content in relevant parts. Conclusions: The results suggest that EA can enhance heart function and ease the depressive state in rats. It indicates that the therapeutic effect of EA on dual heart diseases might result from regulating HIF-1α.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yuan Ma, Lu Ren, and Kexin Zhang "Electro acupuncture regulate heart function and depression state in rats with dual heart disease", Proc. SPIE 13270, International Conference on Future of Medicine and Biological Information Engineering (MBIE 2024), 1327016 (11 September 2024); https://doi.org/10.1117/12.3048284
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KEYWORDS
Heart

Cardiovascular disorders

Tissues

Medicine

Proteins

Statistical modeling

Animals

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